auto adjust legend size on heatmap

SCRIPTS/DE/clusterHeatmap.R

@@ -44,7 +44,7 @@ ecrire<-function(x,file="default.tsv",headRow="Name"){
 }
 
 # specific function
-unsupervisedClustering<-function(x,transpose=TRUE,method.dist="pearson",method.hclust="ward.D2",bootstrap=FALSE,nboot=10){
+unsupervisedClustering<-function(x, transpose=TRUE, method.dist="pearson", method.hclust="ward.D2", bootstrap=FALSE, nboot=10){
         if(transpose) x<-t(x)
         if(bootstrap){
                 require(pvclust)
@@ -92,49 +92,92 @@ plateBatch<-FALSE; if(plateBatchCol %in% colnames(sampleAnnot)) plateBatch<-TRUE
 
 if(batchEffect || plateBatch){
         exprDatT=lire(paste(outputDir,"/exprTransformedAdjusted.tsv",sep=""))
-}else{
+} else {
         exprDatT=lire(exprDatTFile)
 }
 
 annot<-sampleAnnot
 
-corSample<-cor(exprDatT,method = "pearson")
-clustSamples<-unsupervisedClustering(corSample,bootstrap = bootstrap,nboot=nboot,method.dist = "euclidean")
+corSample <- cor(exprDatT, method = "pearson")
+clustSamples <- unsupervisedClustering(corSample,
+                                       bootstrap = bootstrap,
+                                       nboot = nboot,
+                                       method.dist = "euclidean")
 
-colTopAnnot<-vector("list", ncol(annot))
-names(colTopAnnot)<-colnames(annot)
-colFun<-c(ggplotColours,rainbow,topo.colors)
-i<-1
+colTopAnnot <- vector("list", ncol(annot))
+names(colTopAnnot) <- colnames(annot)
+colFun <- c(ggplotColours, rainbow, topo.colors)
+i <- 1
 for(col in colnames(annot)){
-	colTopAnnot[[col]]<-colFun[[i]](nlevels(annot[,col]))
-	names(colTopAnnot[[col]])<-levels(annot[,col])
-	i<-i+1
-	if(i==4) i<-1
+	colTopAnnot[[col]] <- colFun[[i]](nlevels(annot[,col]))
+	names(colTopAnnot[[col]]) <- levels(annot[,col])
+	i <- i+1
+	if(i==4) i <- 1
 }
 
-ha<-HeatmapAnnotation(df = annot, col = colTopAnnot)
+annot_legend_params = vector("list", ncol(annot))  #Calcule automatiquement la taille de police selon le nombre de colonnes ou lignes (empirique)
+names(annot_legend_params) <- colnames(annot)
+default_ft <- 10
+for(col in colnames(annot)){
+        ftsize <- min(default_ft, default_ft*40/nlevels(annot[,col]))
+        if (ftsize < default_ft){
+                annot_legend_params[[col]] <- list(labels_gp = gpar(fontsize = ftsize),
+                                                   grid_height = unit(4*ftsize/default_ft, "mm"), grid_width = unit(4*ftsize/default_ft, "mm")
+                                                  )
+        } else {
+                annot_legend_params[[col]] <- list(labels_gp = gpar(fontsize = ftsize))
+        }
+}
 
-Ht<-Heatmap(matrix = corSample, cluster_rows = clustSamples, cluster_columns = clustSamples, top_annotation = ha,name="Pearson\ncorrelation",row_names_gp = autoGparFontSizeMatrix(ncol(corSample)),column_names_gp = autoGparFontSizeMatrix(ncol(corSample)),row_dend_reorder = FALSE, column_dend_reorder = FALSE,col=heat.colors(100))
 
-Htc<-Heatmap(absSamples[clustSamples$labels,"TotalCount"], name = "Total\nexpression",col=colorRamp2(c(0,max(absSamples$TotalCount)),c("black","green")), show_row_names = FALSE, width = unit(5, "mm"))
+ha<-HeatmapAnnotation(df = annot, col = colTopAnnot, annotation_legend_param = annot_legend_params)
 
-pdf(file = paste(outputDir,"/HeatmapCorPearson.pdf",sep=""),width=10,height=9)
+Ht<-Heatmap(matrix = corSample,
+            cluster_rows = clustSamples,
+            cluster_columns = clustSamples,
+            top_annotation = ha,
+            name = "Pearson\ncorrelation",
+            row_names_gp = autoGparFontSizeMatrix(ncol(corSample)),
+            column_names_gp = autoGparFontSizeMatrix(ncol(corSample)),
+            row_dend_reorder = FALSE,
+            column_dend_reorder = FALSE,
+            col = heat.colors(100))
+
+Htc<-Heatmap(absSamples[clustSamples$labels,"TotalCount"],
+             name = "Total\nexpression",
+             col=colorRamp2(c(0, max(absSamples$TotalCount)), c("black", "green")),
+             show_row_names = FALSE,
+             width = unit(5, "mm"))
+
+pdf(file = paste(outputDir,"/HeatmapCorPearson.pdf", sep=""), width=10, height=9)
 
 print(Ht+Htc)
 
 if(batchEffect || plateBatch){
 	#il y a eu une correction batch
 	exprDat=lire(paste(outputDir,"/exprTransformed.tsv",sep=""))
-	corSampleUnadjust<-cor(exprDat,method = "pearson")
-	clustSamplesUnadjust<-unsupervisedClustering(corSampleUnadjust,nboot=nboot,bootstrap = bootstrap,method.dist = "euclidean")
-
-	Htna<-Heatmap(matrix = corSampleUnadjust, cluster_rows = clustSamplesUnadjust, cluster_columns = clustSamplesUnadjust, top_annotation = ha,name="Pearson\ncorrelation\nnon adjusted",row_names_gp = autoGparFontSizeMatrix(ncol(corSampleUnadjust)),column_names_gp = autoGparFontSizeMatrix(ncol(corSampleUnadjust)),row_dend_reorder = FALSE, column_dend_reorder = FALSE,col=heat.colors(100))
+	corSampleUnadjust <- cor(exprDat,method = "pearson")
+	clustSamplesUnadjust <- unsupervisedClustering(corSampleUnadjust,
+                                                       nboot = nboot,
+                                                       bootstrap = bootstrap,
+                                                       method.dist = "euclidean")
+
+	Htna<-Heatmap(matrix = corSampleUnadjust,
+                      cluster_rows = clustSamplesUnadjust,
+                      cluster_columns = clustSamplesUnadjust,
+                      top_annotation = ha,
+                      name = "Pearson\ncorrelation\nnon adjusted",
+                      row_names_gp = autoGparFontSizeMatrix(ncol(corSampleUnadjust)),
+                      column_names_gp = autoGparFontSizeMatrix(ncol(corSampleUnadjust)),
+                      row_dend_reorder = FALSE,
+                      column_dend_reorder = FALSE,
+                      col = heat.colors(100))
 	print(Htna+Htc)
 }
 dev.off()
 
-png(paste(outputDir,"/HeatmapCorPearson.png",sep=""),width=25,height=22,units="cm",res=600)
+png(paste(outputDir,"/HeatmapCorPearson.png",sep=""), width=25, height=22, units="cm", res=600)
 print(Ht+Htc)
 dev.off()
 
-save(ha,batchEffect,plateBatch,sampleAnnot,file=paste(outputDir,"/heatmap.RData",sep=""))
+save(ha, batchEffect, plateBatch, sampleAnnot, file=paste(outputDir, "/heatmap.RData", sep=""))